extraction_cache_clear
Очистить кэш extraction.
This record as markdown: /tools/llm-agent-sniffer-integration/extraction-cache-clear.md
What extraction_cache_clear does on Llm Agent Sniffer Integration
AI agents call extraction_cache_clear to permanently remove resources in Llm Agent Sniffer Integration, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why extraction_cache_clear is rated Critical
An AI agent that decides to call extraction_cache_clear doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Llm Agent Sniffer Integration is gone. There is no undo for destructive operations.
Attacks that exploit this kind of access
The rule that runs extraction_cache_clear safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Llm Agent Sniffer Integration, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For extraction_cache_clear, this is the rule to start with:
extraction_cache_clear is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Llm Agent Sniffer Integration, apply this rule, and every extraction_cache_clear call is checked against it from then on.
Questions about extraction_cache_clear
Очистить кэш extraction. It is categorised as a Destructive tool in the Llm Agent Sniffer Integration MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Llm Agent Sniffer Integration MCP server in PolicyLayer and add a rule for extraction_cache_clear: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Llm Agent Sniffer Integration. Nothing to install.
extraction_cache_clear is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the extraction_cache_clear rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for extraction_cache_clear. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
extraction_cache_clear is provided by the Llm Agent Sniffer Integration MCP server (mobstardos/llm-agent-sniffer-integration). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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